Sentence examples for predictions of gene from inspiring English sources
Future prospects to advance analysis of gene function include coupling phylogenomic analyses with computational predictions of gene function.
Despite the availability of whole-genome sequences for almost all model organisms, making faithful predictions of gene expression levels based solely on the corresponding promoter sequences remains a challenge.
ZFAP combines functionalities to allow scanning through 3D data sets, searching of images by anatomical terms, predictions of gene expression from literature analysis, and facilitation of the identification of relevant literature through assisted searching of the NCBI PubMed resource.
Genome-scale metabolic models provide a valuable framework to interpret essentiality screens as they allow predictions of gene essentiality using current knowledge of the metabolic network whilst also providing an insight into incomplete or incorrect metabolic knowledge.
The latter false predictions of gene knockouts required to achieve auxotrophy may result from genetic down regulation of these genes that is not explicitly accounted for in the metabolic network model.
Predictions of gene expression signatures developed on frozen material (Intrinsic subtype, Genomic Grade Index, 70 gene signature) showed a high level of concordance between FFPE and FF matched pairs.
We have implemented a table of predictions of gene-disease relationships extracted from the PhenoPred tool developed at Indiana University [29].
a matrix of predictions of gene-disease relationships based on known relationships mined from the literature and machine learning predictions [29].
A link to the bioassay along with the bioassay name is given, and an additional column uses the extraction of Gene Ontology terms from the bioassay description along with the PhenoPred predictions of gene-disease relationships to list possible related diseases.
We validate our predictions of gene-level expression resulting from the cross-hybridization correction using ultra high-throughput sequencing data.
These resources comprised annotation databases, gene sequences, public gene expression data, PPI databases, putative transcription factors binding sites, abstracts and computational predictions of gene-disease associations.
